Is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K good for coding?

In our benchmarks, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K scores 61.5/100 for coding. It runs at about 42.0 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).

Is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K good for agentic (tool-using) tasks?

In our benchmarks, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K scores 79.6/100 for agentic workflows. It runs at about 42.0 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).

How fast is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K for local inference?

Across 10 community benchmark runs, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K reaches up to 43.0 tok/s and averages 42.0 tok/s, with the fastest results on NVIDIA GeForce RTX 4060 Laptop GPU.

Which tools have been used to run NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K?

Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.

Model benchmarks

NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K local LLM performance

As of October 2026, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K runs at up to 43.0 tok/s for local inference (best of 10 community benchmark runs across 1 GPU).

llama.cppQ6_K

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Model size

Peak speed

43.0 tok/s

Average speed

42.0 tok/s

Avg PP

812.8 tok/s

Min memory

n/a

Max context

32,768 tokens

Avg output / run

7,799 tokens

Avg runtime / run

3m 13s

Avg quality

70.9

Benchmark runs

GPUs tested

Quality by task

Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 10 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.

Task	P5 (low)	Avg	P95 (high)
Overall	65.9	70.9	76.0
Agent Workflow	68.3	79.6	88.6
Code Generation	47.5	61.5	70.6
Role Play & Narrative	74.8	80.7	89.6
Research & Analysis	48.5	61.5	69.7

Performance by hardware and tool

Every hardware/tool/quantization combination NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.

Hardware	Tool	Quant	Best tok/s	Avg tok/s	Memory	Context	Quality	Runs
NVIDIA GeForce RTX 4060 Laptop GPU	llama.cpp	Q6_K	43.0 tok/s	42.0 tok/s	n/a	32,768 tokens	70.9	10

Benchmark runs

All 10 NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K good for coding?: In our benchmarks, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K scores 61.5/100 for coding. It runs at about 42.0 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
Is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K good for agentic (tool-using) tasks?: In our benchmarks, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K scores 79.6/100 for agentic workflows. It runs at about 42.0 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
How fast is NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K for local inference?: Across 10 community benchmark runs, NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K reaches up to 43.0 tok/s and averages 42.0 tok/s, with the fastest results on NVIDIA GeForce RTX 4060 Laptop GPU.
Which tools have been used to run NVIDIA-Nemotron-3.5-Bolt-E4B-Q6_K?: Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.